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Bastian Wiesner
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initial validation and verification implementation using unit tests
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‎data/vv_scenarios.csv‎

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description,model,threshold,hysteresis,region,start_times_set,historical,overhead_budget_pct
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Verification baseline - no pause,Deepseek,"1000","900",CN,"01-01","2024",200
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Verification baseline - no pause DE,Deepseek,"1000","900",DE,"01-01","2024",200
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Verification baseline - no pause SE,Deepseek,"1000","900",SE,"01-01","2024",200
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Verification baseline - no pause US,Deepseek,"1000","900",US,"01-01","2024",200
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Verification pause with known pattern,Deepseek,"400","350",CN,"01-01","2024",200
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Verification policy control - loose,Deepseek,"500","450",DE,"01-01","2024",200
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Verification policy control - medium,Deepseek,"350","300",DE,"01-01","2024",200
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Verification policy control - aggressive,Deepseek,"250","200",DE,"01-01","2024",200
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Validation regional realism Germany,Deepseek,"350","300",DE,"01-01","2024",200
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Validation regional realism Sweden,Deepseek,"25","20",SE,"01-01","2024",200
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Validation temporal realism summer,Deepseek,"350","300",DE,"06-01","2024",200
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Validation temporal realism winter,Deepseek,"350","300",DE,"01-01","2024",200
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Validation trade-off frontier p1,Deepseek,"500","450",DE,"01-01","2024",200
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Validation trade-off frontier p2,Deepseek,"400","350",DE,"01-01","2024",200
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Validation trade-off frontier p3,Deepseek,"300","250",DE,"01-01","2024",200
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Validation trade-off frontier p4,Deepseek,"200","150",DE,"01-01","2024",200
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Validation threshold sweep 250,Deepseek,"250","200",DE,"01-01","2024",200
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Validation threshold sweep 300,Deepseek,"300","250",DE,"01-01","2024",200
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Validation threshold sweep 350,Deepseek,"350","300",DE,"01-01","2024",200
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Validation threshold sweep 400,Deepseek,"400","350",DE,"01-01","2024",200
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Validation cross-model baseline Deep,Deepseek,"1000","900",US,"01-01","2024",200
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Validation cross-model baseline Kimi,Kimi,"1000","900",US,"01-01","2024",200
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Validation cross-model policy Deep,Deepseek,"400","350",US,"01-01","2024",200
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Validation cross-model policy Kimi,Kimi,"400","350",US,"01-01","2024",200
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Deepseek training in US,Deepseek,"400,450","350,400",US,"01-01,06-01,08-08","2022,2023,2024,2025",200

‎output/vv_results.csv‎

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scenario_description,model,region,historical_years,start_time,threshold,hysteresis_margin,total_wall_time_h,training_time_h,paused_time_h,checkpoint_overhead_h,total_energy_kwh,training_energy_kwh,paused_energy_kwh,checkpoint_energy_kwh,total_emissions_kgco2,tokens_processed,tokens_total,completed,num_pauses,overhead_budget_pct,actual_overhead_pct,within_overhead_budget,timestamps,carbon_intensity_series,state_series,emissions_series,tokens_remaining_series,baseline_emissions_kgco2,baseline_time_h,issues,stop_reason,co2_savings_pct
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Deepseek training in US,Deepseek,US,"[2022, 2023, 2024, 2025]",1970-01-01T00:00:00Z,400.0,350.0,3445.6666666666665,844.0833333333334,2600.8806666666674,0.7026666666666668,1943965.4109182577,1536798.8906667966,405887.1947266272,1279.3255253333332,724029.493475334,9603792591092,14800000000000,False,17,200.0,200.00160160160166,False,[],[],[],[],[],1011189.9310230978,1300.8333333333333,['Overhead 200.0% exceeds budget 200%'],budget_exceeded,28.398269082567083
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Deepseek training in US,Deepseek,US,"[2022, 2023, 2024, 2025]",1970-01-01T00:00:00Z,450.0,400.0,1964.3333333333333,1300.7812502032423,663.4280831300912,0.12400000000000001,2472054.758124121,2368296.0003702566,103532.99442586783,225.763328,980301.3770727289,14800000000000,14800000000000,True,3,200.0,51.01181179618719,True,[],[],[],[],[],1011189.9310230978,1300.8333333333333,[],completed,3.054673805851349
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Deepseek training in US,Deepseek,US,"[2022, 2023, 2024, 2025]",1970-06-01T00:00:00Z,400.0,350.0,2601.5833333333335,0.0,2601.542,0.04133333333333333,406065.65526209417,0.0,405990.4008194274,75.25444266666668,180045.41472419823,0,14800000000000,False,1,200.0,200.0016016016016,False,[],[],[],[],[],1035334.306760919,1300.8333333333333,['Overhead 200.0% exceeds budget 200%'],budget_exceeded,82.60992477999915
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Deepseek training in US,Deepseek,US,"[2022, 2023, 2024, 2025]",1970-06-01T00:00:00Z,450.0,400.0,3128.3333333333335,526.75,2601.4179999999997,0.16533333333333333,1365311.0434460363,959038.9759999175,405971.0496770274,301.0177706666667,579094.9899315856,5993244443508,14800000000000,False,4,200.0,200.00160160160155,False,[],[],[],[],[],1035334.306760919,1300.8333333333333,['Overhead 200.0% exceeds budget 200%'],budget_exceeded,44.066859742791166
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Deepseek training in US,Deepseek,US,"[2022, 2023, 2024, 2025]",1970-08-08T00:00:00Z,400.0,350.0,2601.5833333333335,0.0,2601.542,0.04133333333333333,406065.65526209417,0.0,405990.4008194274,75.25444266666668,172978.56627138535,0,14800000000000,False,1,200.0,200.0016016016016,False,[],[],[],[],[],1050536.8745916141,1300.8333333333333,['Overhead 200.0% exceeds budget 200%'],budget_exceeded,83.53426990950422
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Deepseek training in US,Deepseek,US,"[2022, 2023, 2024, 2025]",1970-08-08T00:00:00Z,450.0,400.0,2970.6666666666665,1300.7812502032423,1669.5134164634248,0.37199999999999994,2629513.547295539,2368296.0003702566,260540.25694117657,677.2899840000001,1073316.3188628163,14800000000000,14800000000000,True,9,200.0,128.37557555995096,True,[],[],[],[],[],1050536.8745916141,1300.8333333333333,[],completed,-2.1683621795815102

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